Joint inversion of microwave and ultrasonic data for breast imaging is investigated with deterministic edge-preserving regularization by introducing auxiliary variables indicating whether a pixel is on an edge or not. These edge markers are shared by dielectric and acoustic parameters and are the link to fusion between modalities. They can be jointly optimized from the last parameter profiles of microwave and ultrasonic cases and guide the next optimization as coefficients of the regularization term. Alternate minimization is used to update acoustic contrast, edge markers and dielectric contrast. Comprehensive numerical experiments are carried out on breast phantoms, a simple synthetic one and three extracted from a database. The results show, with comparisons to more classical approaches involving total variation or cross-gradient regularization developed in parallel, that the joint inversion algorithm can gain from the high resolution of ultrasonic imaging and the high contrast of microwave imaging. The quality of microwave imaging is enhanced in clear fashion and small tumors detected.

中文翻译：

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乳腺成像中具有边缘保留正则化的电磁和声学数据联合反演


通过引入指示像素是否位于边缘的辅助变量，利用确定性边缘保留正则化研究了用于乳腺成像的微波和超声数据的联合反演。这些边缘标记由介电和声学参数共享，并且是模态之间融合的链接。它们可以根据微波和超声情况的最后参数曲线进行联合优化，并作为正则化项的系数来指导下一步优化。交替最小化用于更新声学对比度、边缘标记和介电对比度。对乳房模型（从数据库中提取的一个简单的合成模型和三个模型）进行了全面的数值实验。结果表明，与并行开发的涉及全变分或交叉梯度正则化的更经典方法相比，联合反演算法可以从超声成像的高分辨率和微波成像的高对比度中获益。微波成像的质量以清晰的方式得到提高，并且可以检测到小肿瘤。